Two key challenges slow down model convergence in DL. These are slow spread of information resulting in weight update delays and local data heterogeneity [1]}. Several weight aggregation schemes have been proposed to tackle data heterogeneity in the FL setting. These include FedProx [2]}, FedNova [3]}, SCAFFOLD [4]}. Likewise, several algorithmic solutions have been proposed to tackle data heterogeneity under the DL setting [5]}, [6]}, [7]}.
